Senior Data Engineer Job Details | Vail Resorts

Vail Resorts is a leading company in the hospitality industry, focused on creating exceptional experiences for both employees and guests. They are seeking a Senior Data Engineer to architect and maintain high-efficiency data assets that enhance marketing analytics capabilities and drive cross-functional partnerships within the organization.

Responsibilities:

• Architect & Scale Data Pipelines: Design, build, and maintain robust, scalable ingestion pipelines from a diverse suite of marketing sources (APIs, SFTPs, webhooks etc.), ensuring high availability and data integrity
• Optimize Core Data Assets: Develop, maintain, and tune high-performance dbt models to transform raw marketing data into production-ready analytic assets for cross-functional reporting
• Drive Infrastructure Efficiency: Audit and refactor existing data infrastructure to uncover cost efficiencies and optimize compute performance across marketing data sets
• Accelerate AI Readiness: Develop and scale semantic layers and data models specifically tailored to fuel downstream AI use cases and predictive marketing analytics
• Champion Governance & Literacy: Author comprehensive data documentation, lineage maps, and artifacts to elevate data literacy and foster a culture of self-service across the organization
• Lead Cross-Functional Partnerships: Act as the primary engineering partner to the Marketing Analytics team, translating complex business requirements into high-impact, performant data products
• Bridge IT & Engineering: Collaborate closely with IT and core Data Engineering teams to align architectural standards, bridge capability gaps, and foster a cohesive, modern data ecosystem
• Serve as a Subject Matter Expert: Act as a key technical resource for data engineering best practices, scalable architectural design, and marketing data usage
• Drive Technical Excellence & Mentorship: Act as a technical mentor to elevate the team's engineering capabilities, driving continuous skill development and championing modern best practices across analytics and engineering cohorts

Requirements:

• B.S. degree in a quantitative field (e.g., Computer Science, Mathematics, Statistics, Economics, Operations Research, Engineering)
• Proven ability to write clean, modular, testable, and maintainable code
• Deep understanding of how to architect production-grade systems over one-off scripts or notebooks
• Strong in Python and SQL for building data pipelines, automation, model integrations, analytical workflows, and production services
• Hands-on experience managing and processing large-scale digital marketing datasets (log-level website, application, and paid media data) efficiently across cloud infrastructure
• Experience implementing Medallion architecture and a solid understanding of data warehouse design and schema structuring
• Expert-level knowledge of dbt (Core) for modular data modeling, including strict enforcement of schema testing, documentation, and complex dependency management
• Proficient with Git workflows (branching strategies, pull requests, code reviews) and integrating pipelines into automated CI/CD deployment workflows
• Bring intellectual curiosity, an inquisitive nature, and a desire to deepen your knowledge and continue learning
• Take responsibility to proactively advance projects, contribute to the organization, and develop the best solutions
• Take initiative to understand full scope of business problems and propose solutions ahead of being directly asked
• Explain technical concepts, risks, tradeoffs, and recommendations clearly to technical and non-technical audiences
• Work effectively cross-functionally with data scientists, data engineers, analysts, application engineers, product partners, and business stakeholders
• A graduate degree (Masters or PhD) in a quantitative field
• Deep experience with Databricks, especially Unity Catalog, Delta Lake, Databricks Workflows, job/cluster optimization, and governance
• Experience using Spark or similar distributed frameworks to build or support scalable data
• Experience with data visualization tools such as Tableau or Power BI